異質(zhì)系統(tǒng)架構(gòu)(Heterogeneous Systems Architecture，HSA)基金會(huì)在那個(gè)對(duì)未來的處理器 SoC 設(shè)計(jì)工程師與相關(guān)軟件非常重要的新技術(shù)領(lǐng)域取得了不錯(cuò)進(jìn)展，但該技術(shù)要取得成功恐怕還有一段很長的路要走。
日前 AMD 宣布將在明年1月推出首款采用 HSA 技術(shù)的處理器；該架構(gòu)能讓中央處理器(CPU)與繪圖處理核心共享資源。AMD以Linux為基礎(chǔ)開發(fā)了支持新架構(gòu)的軟件，但到目前為止并未有其它支持HSA的處理器或操作系統(tǒng)計(jì)劃公布。
包 括ARM、Imagination、聯(lián)發(fā)科(Mediatek)、高通(Qualcomm)與三星( Samsung)等移動(dòng)處理器大廠與核心供貨商，也都是HSA基金會(huì)的成員；在一場日前于美國舉行的AMD開發(fā)者大會(huì)上，一位來自Imagination 的高層表示，該公司總有一天會(huì)支持HSA架構(gòu)，但他并未透露相關(guān)產(chǎn)品的推出時(shí)間表。
ARM 首席技術(shù)官M(fèi)ike Muller的態(tài)度更為保守，他在會(huì)中表示：“HSA對(duì)中型系統(tǒng)來說很好，但我不確定它是否能適用最小型的系統(tǒng)，我也不認(rèn)為它能支持內(nèi)含上萬顆處理器的高性能運(yùn)算。單一系統(tǒng)的架構(gòu)不會(huì)擴(kuò)展到整個(gè)應(yīng)用空間?！?
蘋果(Apple)、Google與微軟(Microsoft)則對(duì)他們?cè)趇OS、Android與Chrome OS，還有Windows等操作系統(tǒng)對(duì)HSA的支持三緘其口；目前設(shè)計(jì)工程師雖然能撰寫驅(qū)動(dòng)程序以在Windows等操作系統(tǒng)支持該架構(gòu)，但并沒有更理想的解決方案。
而最與眾不同的是AMD的競爭對(duì)手英特爾(Intel)與Nvidia，這兩家公司與蘋果都在移動(dòng)與臺(tái)式計(jì)算機(jī)系統(tǒng)支持 OpenCL；由Khronos Group開發(fā)的 OpenCL 規(guī)格是針對(duì)各種繪圖處理器(GPU)之平行編程任務(wù)所開發(fā)的較高層級(jí)應(yīng)用程序接口(API)。
OpenCL 已經(jīng)存在好一段時(shí)間，但才剛開始加入一些HSA基金會(huì)正在定義的共享內(nèi)存功能。一位Khronos 與Nvidia的代表就指出，HSA、OpenCL以及Nvidia專有的Cuda軟件環(huán)境，其實(shí)是朝平行路線發(fā)展，并提供越來越類似的功能。
Cuda是Nvidia在高性能運(yùn)算領(lǐng)域的一次成功出擊，曾進(jìn)駐全球前五百大超級(jí)計(jì)算機(jī)；而由于很早就進(jìn)軍高性能運(yùn)算領(lǐng)域，市場上有越來越多采用Nvidia配備Cuda之GPU的系統(tǒng)。但這樣的情況也可能會(huì)改變。
高性能運(yùn)算領(lǐng)域?qū)＜?、美國伊利諾大學(xué)(University of Illinois)計(jì)算機(jī)科學(xué)教授Wen-mei Hwu表示：“超級(jí)計(jì)算機(jī)開發(fā)商每三到四年就會(huì)去找新東西、選定其中某個(gè)，然后在幾年后實(shí)際運(yùn)用?！弊钚掳娴腃uda已經(jīng)可以支持部分HSA的平面內(nèi)存 (flat-memory)功能，但Cuda并不怎么適合一些超級(jí)計(jì)算機(jī)應(yīng)用程序，這就為HSA基金會(huì)與AMD帶來機(jī)會(huì)。
至于英特爾則在高階運(yùn)算領(lǐng)域有自己的方案，其 Xeon Phi 處理器采用60個(gè)簡化的 x86核心來處里平行任務(wù)，搭配該公司自家開發(fā)的工具； Phi 已經(jīng)開始獲得一些全球五百大超級(jí)計(jì)算機(jī)開發(fā)商的青睞(而且是在短時(shí)間內(nèi))。
本文授權(quán)編譯自EE Times，版權(quán)所有，謝絕轉(zhuǎn)載
本文下一頁：HSA的甜蜜點(diǎn)在哪？
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• Tensilica加入HSA基金會(huì)，助力嵌入式異構(gòu)計(jì)算標(biāo)準(zhǔn)建立
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HSA將擴(kuò)展至GPU以外的處理器
HSA的甜蜜點(diǎn)在于能解決主流運(yùn)算領(lǐng)域一些非常實(shí)際的問題，而該領(lǐng)域有越來越多看起來像是配備各種核心的智能手機(jī)芯片。
“我們一直很謹(jǐn)慎開發(fā)能支持各種加速處理器的(HSA)架構(gòu)，”HSA基金會(huì)總經(jīng)理、專長繪圖處里的AMD院士Phil Rogers表示：“我們是以GPU為第一步，而其它種類的加速處理器是可以預(yù)期的，包括DSP、DMA引擎、譯碼器以及加密處理器；只要是合理的，每一 家公司都將會(huì)轉(zhuǎn)向開發(fā)加速處理器?！?
HSA為程序開發(fā)者解決了非常實(shí)際的問題；如Rogers所言，當(dāng)處理器的CPU與GPU核心擁有各自的內(nèi)存時(shí)，要在處理器SoC上操作主流應(yīng)用程序會(huì)有許多困難：“人們已經(jīng)開發(fā)了利用兩組處理器核心的應(yīng)用程序，但問題在于它們是用很不自然的方式才能運(yùn)作?！?
Rogers表示，如果虛擬內(nèi)存空間中存在只有CPU能理解的“指針(pointers)”，要橫跨現(xiàn)有的不同資料架構(gòu)幾乎是不可能的。因此今日的移動(dòng)應(yīng)用程序設(shè)計(jì)工程師，通常得重新打造資料架構(gòu)，以保持追蹤不同 CPU 與 GPU 核心的資料。
在 專題演說中，Rogers提到了可利用HSA帶來之額外性能與簡易性的各種應(yīng)用程序，例如在Hadoop與Map Reduce平臺(tái)上執(zhí)行的大型資料中心、特定的數(shù)據(jù)庫任務(wù)、石油天然氣探勘，以及電信營運(yùn)商與網(wǎng)絡(luò)資料中心的媒體轉(zhuǎn)碼(media transcoding)。
因此HSA能為處理器與應(yīng)用程序開發(fā)商帶來實(shí)際的優(yōu)勢，還有AMD──如果該公司能藉由某種方式 提供超越英特爾與Nvidia方案的獨(dú)特功能。而由于在電子學(xué)方面還有許多問題存在，一切只能等待。AMD早在2006年為了GPU收購ATI時(shí)，就看好 微處理器的未來是混合式核心SoC；七年后，該公司仍堅(jiān)持初衷，但要實(shí)現(xiàn)該愿景，還有好一段路得走。
本文授權(quán)編譯自EE Times，版權(quán)所有，謝絕轉(zhuǎn)載
編譯：Judith Cheng
參考英文原文：AMD Faces Long Road to HSA Success，by Rick Merritt
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• 聯(lián)發(fā)科新八核芯片將成導(dǎo)入HSA技術(shù)試金石
• Tensilica加入HSA基金會(huì)，助力嵌入式異構(gòu)計(jì)算標(biāo)準(zhǔn)建立
• AMD發(fā)布X86/ARM架構(gòu)混搭處理器，目標(biāo)筆電和平板rgbesmc
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AMD Faces Long Road to HSA Success
Rick Merritt
SAN JOSE, Calif. — The Heterogeneous Systems Architecture (HSA) Foundation is making good progress in an area important for future designers of SoCs and the software that rides on them, but it still faces a long road to success.
This week, Advanced Micro Devices said it will ship the first processor to use HSA techniques of letting CPU and graphics cores share resources in January. AMD developed support under Linux for the techniques, but no other plans have been announced so far for processors or operating systems supporting the techniques. The chips (and probably the operating systems) will come at some point.
ARM, Imagination, Mediatek, Qualcomm, Samsung, and other top mobile SoC and core designers are part of HSA. During a panel discussion at AMD's developer conference here, an Imagination executive said the company will support HSA on all its cores eventually, but he would not give say which cores would ship when. ARM CTO Mike Muller was more reserved. "HSA is good for midrange systems, but I'm not sure if it scales to the smallest systems, and I don't think it does scale to high-performance computing with tens of thousands of processors," he said during the panel discussion. "One system's architecture won't scale across the whole space."
Apple, Google, and Microsoft have remained mum about their plans to support HSA in iOS, Android, Chrome OS, and Windows. Designers can write drivers to support the techniques in operating systems such as Windows, but that's not an ideal approach.
The big standouts are AMD's archrivals: Intel and Nvidia. They and Apple back OpenCL in mobile and desktop systems. The Khronos Group's OpenCL spec is a higher-level API for programming parallel tasks on any GPU. It has been around for a while but is just starting to build in some of the shared-memory goodies the HSA Foundation is defining.
A representative for Khronos and Nvidia said HSA, OpenCL, and Nvidia's proprietary Cuda software environment are on parallel paths and offering increasingly similar features.
Cuda has been a hit for Nvidia in high-performance computing, including in the top 500 supercomputers. Thanks to an early move into this market, a growing share of these systems use Nvidia's GPUs with Cuda. But that could change.
"Every three or four years, supercomputer developers look around for what's new, seize on something, and really milk it for a few years," said Wen-mei Hwu, a professor of computer science at the University of Illinois and an expert in the field. The latest versions of Cuda already support some HSA flat-memory features. But Cuda is not well suited for some supercomputer apps, and that could open a door for the HSA Foundation and AMD.
Intel does Phi, AMD beyond GPUs
Intel has its own offering at the high end. Its Xeon Phi uses more than 60 simplified x86 cores to handle parallel jobs, using tools Intel has developed. Phi is just starting to gain traction (quite quickly) among the top 500.
The sweet spot for HSA is solving very real problems in the mainstream computing space, where processors are increasingly looking like smartphone chips with a variety of cores.
"We've been careful to develop an [HSA] architecture that works for all accelerators," said Phil Rogers, president of the HSA Foundation and an AMD fellow with a specialty in graphics. "We started first with GPUs, but other accelerators are expected, including DSPs, DMA engines, codecs, and crypto processors. Each company will migrate to accelerators as it makes sense."
The programmer's problem HSA solves is very real. Rogers talked about the difficulties handling mainstream apps on SoCs where CPU and GPU cores have their own private pools of memory. "People already developing apps that use both sets of cores, but the problem is they have to perform unnatural acts to make it work." It's nearly impossible to "walk through the data structures that exist if they have pointers that are in the virtual memory space only the CPU understands."
Thus today's mobile programmers typically recraft data structures to keep track of information in various CPUs and GPUs. In addition to creating extra complexity and work, the approach sacrifices some performance. In his keynote, Rodgers talked about all sorts of apps that could use the extra performance and simplicity HSA promises. They include big data jobs run on Hadoop and Map Reduce, certain database tasks, oil and gas discovery, and media transcoding for carriers and web datacenters.
So HSA promises real advantages for developers of SoCs and apps -- and for AMD if it can deliver the features in a way that leapfrogs Intel and Nvidia offerings. As with so many issues in electronics, it comes down to a question of when.
AMD saw the future of microprocessors was in mixed-core SoCs back in 2006, when it purchased ATI Technologies for its GPUs. Seven years later, it is still pursuing the vision, and it still faces a long road to deliver on it.
